SE1630095A1 - Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor - Google Patents

Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor

Info

Publication number
SE1630095A1
SE1630095A1 SE1630095A SE1630095A SE1630095A1 SE 1630095 A1 SE1630095 A1 SE 1630095A1 SE 1630095 A SE1630095 A SE 1630095A SE 1630095 A SE1630095 A SE 1630095A SE 1630095 A1 SE1630095 A1 SE 1630095A1
Authority
SE
Sweden
Prior art keywords
ceacam5
expression levels
determining
metastatic potential
postn
Prior art date
Application number
SE1630095A
Other languages
Swedish (sv)
Other versions
SE540173C2 (en
Inventor
Olsson Lina
Hammarström Sten
Hammarström Marie-Louise
Lindmark Gudrun
Israelsson Anne
Original Assignee
Hiloprobe Ab
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hiloprobe Ab filed Critical Hiloprobe Ab
Priority to SE1630095A priority Critical patent/SE540173C2/en
Priority to CN201780024184.7A priority patent/CN109073651A/en
Priority to EP17786247.1A priority patent/EP3446122B1/en
Priority to US16/093,013 priority patent/US10988811B2/en
Priority to AU2017254347A priority patent/AU2017254347B2/en
Priority to KR1020187029589A priority patent/KR102353374B1/en
Priority to JP2018554694A priority patent/JP6968822B2/en
Priority to PCT/SE2017/050368 priority patent/WO2017184059A1/en
Publication of SE1630095A1 publication Critical patent/SE1630095A1/en
Publication of SE540173C2 publication Critical patent/SE540173C2/en
Priority to US17/210,768 priority patent/US20210246513A1/en

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • G01N33/57419—Specifically defined cancers of colon
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6844—Nucleic acid amplification reactions
    • C12Q1/6851—Quantitative amplification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/112—Disease subtyping, staging or classification
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Landscapes

  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Organic Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Engineering & Computer Science (AREA)
  • Zoology (AREA)
  • Wood Science & Technology (AREA)
  • Immunology (AREA)
  • Analytical Chemistry (AREA)
  • Genetics & Genomics (AREA)
  • Molecular Biology (AREA)
  • Biochemistry (AREA)
  • Microbiology (AREA)
  • Biotechnology (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Biophysics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Hospice & Palliative Care (AREA)
  • Oncology (AREA)
  • Biomedical Technology (AREA)
  • Hematology (AREA)
  • Urology & Nephrology (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Cell Biology (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • General Physics & Mathematics (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

The present invention provides a group of molecular biomarkers, comprising the genes SLC35D3, POSTN, KLK6 and MUC2, for use in objective and quantitative methods for the classification, prediction of prognosis and for guiding treatment decisions of a subject with colorectal cancer. More specifically the present invention provides methods for determining the metastatic potential and/or tumor aggressiveness of a colorectal cancer in a subject, comprising determining the gene expression levels of genes SLC35D3, POSTN, KLK6 and/or MUC2 in a regional lymph node, a primary intestinal tumor, blood, or faeces sample obtained from the subject.

Description

Marker genes for colorectal cancer Classification, method forjudging lymph node metastasis for prognosis of colorectal cancer and kit therefor FIELD OF THE INVENTION The present invention relates to the field of Classification, prognostics and treatment of cancer, in particular colorectal cancer.BACKGROUND Colorectal cancer (CRC) is the second leading cause of mortality among cancer patientsin the world and the third most diagnosed form of cancer globally. It represents a hugeburden on healthcare systems. The most important prognostic characteristic of CRC ispresence or absence oflymph node metastasis (Chang G. ]. et al. ]. Natl. Cancer Inst.,vol.99, p. 433-441 (2007); lddings D. and Bilchik A. ]. Surg. Oncol., vol. 96, p. 671-677(2007); Nicastri D. G. et al. ]. Mol. Diagn., vol. 9, p. 563-571 (2007)). Relevant lymphnodes are accessible for investigation only when patients are resected for cure.Therefore, thorough determination of the lymph node status in the resected tumorspecimen is crucial. Currently, approximately 50 % of patients with tumor-cell-positivelymph nodes, i.e. stage III CRC (anyTN1-2M0) and about 25% with no detected tumor-cell positive lymph nodes, i.e. stage I (T1-2 NOM0) and stage II (T3-4NOM0) patients willrecur (Böckelman C. et al. Acta Oncol., vol. 54, p. 5-16 (2015)). These results stronglysuggest that tumor cells in lymph nodes may vary in aggressiveness, and that presenceof tumor cells in the node in many cases is missed by the present standard method.Therefore it is of utmost importance to 1) accurately detect presence of tumor cells inlymph nodes and 2) determine their metastatic potential i.e. their aggressiveness. Byimproving determination of lymph node status, N-staging, and introducing theaggressiveness parameter for the spread tumor cells, improved staging will be achievedthereby avoiding undertreatment of stage I and II patients and overtreatment of stage III patients. Moreover, if patients with tumor cells in their lymph nodes can be classified into subgroups according to differences in risk of recurrence and cancer death thisinformation may be used not only for treatment with the current arsenal of drugs butalso in the development of new drugs, new treatment schedules as well as for follow-up schedules adjusted to the risk of recurrence, etc.
In clinical practice, presence or absence of lymph node metastasis is currentlydetermined by histopathological examination of hematoxylin 81 eosin (H&E) stainedtissue sections of resected regional lymph nodes. Present guidelines require that at least12 lymph nodes should be examined (Tsai H. L. et al. BMC Surg., vol. 16, p. 17 (2016)) Inthe TNM classification, N1 signifies that 1 to 3 examined nodes were positive forpresence oftumor cells and N2 that 4 to 6 nodes were positive. N2 patients have poorerprognosis than N1 patients. Moreover, the lymph node ratio, i.e., number of positivelymph nodes over total number of examined lymph nodes, is an important prognosticfactor - the higher ratio the worse prognosis (Parnaby C. N. et al, Br. I. Cancer, vol. 113,p. 212-219 (2015)). The main reasons why tumor cells are missed by the routinemethod are twofold: too small sample size and inadequate sensitivity. At best, only a few% of the volume of the lymph node is examined by H&E staining oftissue sections. Analternative method is to determine the mRNA level of one or several biomarkers that isexpressed in all tumor cells of this type, and to extract RNA from the entire lymph nodeor, as for ethical reasons is the current option, half the node. It has been shown that realtime quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysiswith copy standard is a most useful method for mRNA analysis of biomarkers. It ishighly sensitive, objective, quantitative, and amendable for automation. It was foundthat mRNA analysis of the biomarker carcinoembryonic antigen (CEA, CEACAM5) is veryuseful for detection of tumor cells originating from the large intestine. This biomarkerallowed the identification of stage I and stage II patients with tumor cells in their lymphnodes that were not detected by the present gold standard, i.e. histopathology of H&Estained sections (Ohlsson L. et al. Br. I. Cancer, vol. 95, p. 218-225 (2006); Ohlsson L. etal. Int. I. Cancer, vol. 130, p. 1833-1843 (2012)). Some ofthese patients havesuccumbed from recurrent disease (Ohlsson L. et al. Br. I. Cancer, vol. 95, p. 218-225(2006); Ohlsson L. et al. Int. I. Cancer, vol. 130, p. 1833-1843 (2012)). Thus, a moresophisticated stratification was obtained by using this marker compared to the gold standard only. The biomarker cytokeratin 20 (CK20) is also useful for this purpose, albeit somewhat less sensitive (Ohlsson L. et al. Br. ]. Cancer, vol. 95, p. 218-225 (2006).Currently there is only one published biomarker for CRC that displays the properties ofan aggression marker, namely kallikrein related peptidase 6 (KLK6) (Ohlsson L. et al. Br.]. Cancer, vol. 107, p. 150-157 (2012)). lt is ectopically expressed in CRC tumor cells and appears to be expressed at increasing levels with increasing aggressiveness.
A generally accepted pathway for the development of distant metastases in CRC is thattumor cells leave the primary site in colon or rectum via lymphatic vessels, first settle ina regional lymph node, and thereafter, spread to distant sites like the liver. lt is thedistant metastasis that eventually kills the patient. Evidence for this pathway is the factthat presence or absence of tumor cells in a regional lymph node is the best prognostic marker for CRC death or survival.
The present invention concerns: 1) the identification of two new aggression biomarkersfor CRC; one expressed in the CRC tumor cells themselves and the other in supportingcells in the microenvironment ofthe lymph node. 2) A method for determination oflymph node status, which accurately detects presence or absence of tumor cells in thelymph nodes, and in addition provides information on the aggressiveness of these cells.ln the proposed method, quantitative mRNA levels ofthe 2 new biomarkers and 3previously described biomarkers are determined. lf applied for CRC lymph nodeanalysis, it will accurately determine lymph node involvement and allow classification ofCRC patients into different risk groups with respect to risk for recurrence and cancerdeath after the primary treatment, i.e. surgical resection of the tumor. This goal has hitherto not been possible to achieve.
OBIECT OF THE INVENTION It is an object of the present invention to provide a group of molecular biomarkers,which are useful for classification, for prediction of prognosis and for guiding treatment decisions of a subject with colorectal cancer. lt is another object of the present invention to provide objective and quantitativemethods for classifying colorectal cancer in a subject, as well as for using theclassification for predicting prognosis of the subject and for making a treatment decisions for the subject.
DESCRIPTION OF THE INVENTION The present inventors have identified the expression levels of the genes solute carrierfamily 35 member D3 (SLC35D3) (GenBank NM_001008783) and periostin, osteoblastspecific factor (POSTN) (GenBank NM_006475) as molecular biomarkers that can beused for determining the metastatic potential and/or tumor aggressiveness of a colorectal cancer in a subject.
Expression levels ofthe genes SLC35D3 and POSTN can preferable be used togetherwith the expression levels of the gene kallikrein related peptidase 6 (KLK6) ( GenBankNM_002774), and even more preferably also together with the expression level ofthegen mucin 2, oligomeric mucus/gel-forming (MUCZ) (GenBank NM_00245 7) for determining the metastatic potential and/or tumor aggressiveness.
The method can be applied to determine gene expression levels in regional lymph nodesamples obtained from the subject, or in primary intestinal tumor, blood, and/or feces samples obtained from the subject.
The expression levels ofthese genes can be related to the expression level of the genecarcinoembryonic antigen related cell adhesion molecule 5 (CEACAMS) (GenBank NM_004363), which is a known tumor marker, and/or related to the level of 18S rRNA.
Accordingly, one aspect of the present invention provides methods for determining themetastatic potential and/ or tumor aggressiveness of a colorectal cancer in a subject,comprising the steps: a) determining the gene expression levels ofgenes SLC35D3, and POSTN in a regional lymph node sample obtained from the subject; and b) comparing the gene expression levels determined in step a) with reference gene expression levels of the same genes in a reference patient population; wherein higher expression levels ofthe genes SLC35D3 and POSTN compared to thereference are associated with an increased metastatic potential and /or tumor aggressiveness.
Preferably the method can further comprise determining the gene expression level ofthe gene KLK6 in said sample.Accordingly, in one embodiment the first aspect of the present invention providesmethods for determining the metastatic potential and/ or tumor aggressiveness of acolorectal cancer in a subject, comprising the steps:a) determining the gene expression levels ofgenes SLC35D3, POSTN and KLK6 ina regional lymph node sample obtained from the subject; andb) comparing the gene expression levels determined in step a) with referencegene expression levels of the same genes in a reference patient population;wherein higher expression levels ofthe genes SLC35D3, POSTN and KLK6 compared tothe reference are associated with an increased metastatic potential and /or tumor aggressiveness.
Preferably the method can further comprise determining the gene expression level ofthe gene MUC2 in said sample.Accordingly, in another embodiment the first aspect of the present invention providesmethods for determining the metastatic potential and/ or tumor aggressiveness of acolorectal cancer in a subject, comprising the steps:a) determining the gene expression levels ofgenes SLC35D3, POSTN, KLK6 andMUC2 in a regional lymph node sample obtained from the subject; andb) comparing the gene expression levels determined in step a) with referencegene expression levels ofthe same genes in a reference patient population;wherein higher expression levels ofthe genes SLC35D3, POSTN, KLK6 and MUC2compared to the reference are associated with an increased metastatic potential and /or tumor aggressiveness.
Preferably the method can further comprise the steps determining the gene expression level of the gene CEACAM5 and the level of18S rRNA in said sample; based on the results obtained in steps a) and c) calculating the ratiosSLC35D3/CEACAM5, KLK6/CEACAM5, POSTN/18S rRNA, andMUC2/CEACAM5; giving the ratios obtained in step d) the values of (+1) or (0) depending onwhether said ratio is larger than a cut-off value based on the same ratio in saidreference patient population, and where ratios higher than the cut-off valueobtain a value of (+1) and values lower than the cut-off level obtain a value of(0); and calculating an index using the ratios obtained in step e) using the formula [A =SLC35D3/CEACAM5 + KLK6/CEACAM5 + POSTN/18S rRNA -MUC2/CEACAM5]; wherein the index (+3) is associated with very high metastatic potential and /or tumor aggressiveness, the index (+2) and (+1) with high metastatic potential and /or tumor aggressiveness, and the index (0) and (-1) with low metastatic potential and /or tumor aggressiveness.
Said cut-off values can be the ratios ofthe 7th decile of said reference patient population, the ratios of the Bfd quartile of said reference patient population, or the ratios ofthe 8th decile of said reference patient population. ln another aspect the present invention provides methods of determining the metastatic potential and/or tumor aggressiveness of a colorectal cancer in a subject, comprising: a) b) C) determining the gene expression levels ofthe genes SLC35D3, KLK6, MUC2and CEACAM5 in a primary intestinal tumor, blood, or feces sample obtainedfrom the subject; based on the result obtained in step a) calculating the ratiosSLC35D3/CEACAM5, KLK6/CEACAM5 and MUCZ/CEACAMS; andcomparing the ratios determined in step b) with reference ratios calculated from expression levels of the same genes in a reference patient population; wherein the ratios SLC35D3/CEACAM5 and KLK6/CEACAM5 are associated with an increased metastatic potential and/ or tumor aggressiveness and the ratio MUC2/CEACAM5 is associated with decreased metastatic potential and/or tumor aggressiveness.
According to the invention the gene expression levels can be determined by quantifying the amount of mRNA expressed from said genes.
The amount of mRNA can be determined by hybridization, sequencing or quantitative RT-PCR.
More specifically the amount of mRNA can be determined by use of a method selectedfrom microarray and bead array technologies, transcriptome sequencing, real time quantitative RT-PCR, multiplex quantitative RT-PCR.
According to the methods the gene expression levels can be determined using RNA orDNA copy standard and/or the 18S rRNA level can be determined using 18S rRNA standard.
Another aspect of the present invention provides methods for determining theprognosis of a subject diagnosed with colorectal cancer. Said method can comprisedetermining the metastatic potential and/or tumor aggressiveness of a colorectal cancerin a subject using a method according to the present invention.
Said methods can comprise determining that the subject has a good prognosis if themetastatic potential and/ or tumor aggressiveness is low, or determining that the subject has a poor prognosis if the metastatic potential and/ortumor aggressiveness is high. Poor prognosis can be a decrease in the likelihood of survival compared to the good prognosis.
Another aspect of the present invention provides methods for determining thetreatment for a subject diagnosed with colorectal cancer and having a tumor. Saidmethod can comprise determining the metastatic potential and/or tumoraggressiveness of a colorectal cancer in a subject using a method according to thepresent invention and determining the treatment for said subject dependent on the metastatic potential and/ or tumor aggressiveness determined.
The treatment can be to give postoperative treatment, e.g. chemotherapy, to a patient determined to have a high metastatic potential and/ or tumor aggressiveness.
The treatment can be to abstain from postoperative treatment to a patient with a low metastatic potential and/ or tumor aggressiveness.
Another aspect of the present invention provides a kit for determining metastaticpotential and/or tumor aggressiveness of a subject diagnosed with colorectal cancer.The kit can comprise nucleic acid primers and probes for determination of the geneexpression levels, of one or more of the genes CEACAM5, KLK6, POSTN, SLC35D3, andMUC2 and optionally nucleic acid primers and probes for determination of the level of 18S rRNA.
The nucleic acid primers and probes can be selected from those given in Table 1.
The kit can further comprise mRNA, RNA and/ or DNA copy standards.
Another aspect of the present invention provides methods for treatment of colorectalcancer. Said method can comprise determining the metastatic potential and/or tumoraggressiveness ofa colorectal cancer in a subject using a method according to thepresent invention, and treating said subject dependent on the metastatic potential and/or tumor aggressiveness determined.
The treatment can be to give postoperative treatment, e.g. chemotherapy, to a patient determined to have a high metastatic potential and/ or tumor aggressiveness.
The treatment can be to abstain from postoperative treatment to a patient with a low metastatic potential and/ or tumor aggressiveness.
FIGURE LEGENDS Figure 1. Expression levels of CEACAM5, MUC2, KLK6, POSTN and SLC35D3 mRNA inprimary CRC tumors (O) (n = 56) and normal colon tissue (n = 5) (O) Figure 2. (A) SLC35D3 and (B) POSTN mRNA expression levels in lymph nodes ofpatients with stage I to IV CRC and control patients (Ctr). Each of the 166 CRC patients and 23 control patients is represented by the lymph node with the highest mRNA value.
Figure 3. Ratios of biomarker mRNA over CEACAM5 mRNA in lymph nodes frompatients with stage I to IV CRC. Each ofthe 166 patients is represented by the lymphnode with the highest mRNA value and indicated by a filled circle.
Figure 4. Cumulative survival curves according to Kaplan-Meier for CRC patients (n =166). Patients are classified in groups (-1, 0, +1, +2 and +3) based on the mRNA value ofthe biomarkers SLC35D 3, POSTN, KLK6, MUC2 and CEACAM5 and calculated accordingto formula: (Formula A = SLC35D3/CEACAM5+KLK6/CEACAM5+ POSTN/18S rRNA-MUC2/CEACAM5). The 8th decile of the mRNA values for each marker was used toclassify the marker value as positive or negative, giving the former a value of (1) and thelatter a value of (0). The lymph node with the highest CEACAM5 mRNA value was chosen to represent the patient. For further details see text.
Figure 5. Cumulative survival curves according to Kaplan-Meier for CRC patients (n =166). Patients are classified in groups (-1, 0, +1, and +2) based on the mRNA value ofthebiomarkers SLC35D3, KLK6, MUC2 and CEACAM5 and calculated according to formula:(Formula E = SLC35D3/CEACAM5 + KLK6/CEACAM5 - MUC2/CEACAM5). For furtherdetails see legend to Figure 4 and text.
DETAILED DESCRIPTION OF THE INVENTION Identification of genes and gene signatures that are significantly correlated to risk of cancer death in colorectal cancer subjects A gene that is of importance for tumor progression is most likely expressed i in theprimary tumor tissue and in secondary tumors present in a regional lymph nodedraining the intestine. A microarray-search for progression markers was performed byanalyzing RNA from 4 different H&E positive lymph nodes (i.e. tumor cell containinglymph nodes) of 4 patients with stage III CRC plus 3 primary tumors from 3 of thesepatients. RNA from 7 control patients (lymph nodes from 2 ulcerative colitis patients, 1Crohns' colitis patient, 1 colon lipoma patient and 3 normal colon epithelial cellssamples) were also analyzed. CRC samples were compared individually relative to allcontrol samples as one group. The microarray data were filtered by setting statisticalsignificance to P < 0.05, fold change to 2 5, and minimum intensity to 15. In this way anumber of genes that were expressed in most ofthe CRC samples (2 5/7) with a foldchange 2 5 times were identified. Among these were SLC35D3, POSTN and KLK6.
Commercially available real-time qRT-PCR assays were used to verify the microarray results (TaqMan Gene Expression Assays) for POSTN, SLC35D3 and KLK6. In the latter case 3 assays for different splice forms. All three genes were expressed in a panel ofprimary CRC tumors samples (n = 8) while SLC35D3 and KLK6 but not POSTN wereexpressed in all CRC cell lines (n = 5).
Table 1. Primer and probe sequences used in qRT-PCR assays for SLC35D3, POSTN, KLK6, MUCZ, CEACAM5, and 18S rRNA Gene 3' primer sequence 5' primer sequence Probe sequence(reverse) (forward) SLC35D3 AGC ACT CCC GTG ACG TCA TCA CCA CCT CCT GGC AGG AGC CGGTAC C GCG GC CGA(SEQ ID NO: 1) (SEQ ID NO: 2) (SEQ ID NO: 3) POSTN CCC TTG CTT ACT CCC ACA GCT CAG AGT ACA GCT GTC TGC ATTTTT CTC CTT CGT ATA TCG GA(SEQ ID NO: 4) (SEQ ID NO: 5) (SEQ ID NO: 6) KLK6 AAG GTT ATG CTT CCC CTT ATC CAT CCA CAC TGC AAA AAA CCGCAG G CTG TGG GTC AAT CTT CAG GTC(SEQ ID NO: 7) (SEQ ID NO: 8) (SEQ ID NO: 9) MUC2 TAG TGT CCA GCT CCA AAG AGC GAT GCC TCC CGG TTC CAC ATG AGCA TGA TAC ACC AAA (SEQ ID NO: 12)(SEQ ID NO: 10) (SEQ ID NO: 11) CEACAM5 TGT AGC TGT TGC AAA CTG ATA TAG CAG AGG AAG ACT GAC AGTTGC TTT AAG CCC TGG TGT AGT TGT(SEQ ID NO: 13) (SEQ ID NO: 14) (SEQ ID NO: 15) 18S rRNA CCG CTC CCA AGA TCC GTA ATT CCA GCT CTG CAG TTA AAA AGCAA CCA ATA GCG TA (SEQ ID NO: 18)(SEQ ID NO: 16) (SEQ ID NO: 17) Real-time qRT-PCR assays with RNA copy standards using the Taqman EZ RT-PCRtechnology as described (Fahlgren A. et al. Clin. Exp. lmmunol., vol. 131, p. 90-101(2003); Ohlsson L. Thesis, ISBN 978-91-7459-318-1 (2011)) were constructed. Primerand probe sequences for real-time qRT-PCR assays for SLC35D3, POSTN, KLK6, MUC2,and CEA, mRNA are shown in Table 1 and primers for construction of RNA copystandards in Table 2. Using these assays a panel of RNA samples including primary CRCtumors, normal colon tissue and purified colon epithelial cells, CRC cell lines, peripheralblood mononuclear cells (PBMCs), different immune cell lines and a fibroblast cell linewere analyzed (Table 3). The individual values of 56 primary CRC tumors and 5 normalcolon samples are shown in Figure 1. For comparison the result for CEACAM5 andMUC2 is included (Ohlsson L. Thesis, ISBN 978-91-7459-318-1 (2011)). lt is apparentthat all five biomarker mRNAs are expressed in primary CRC tumors, although at highlydifferent copy number levels normalized to the 18S rRNA content in the sample, from amedian of 164 for CEACAM5 to 0.17 for SLC35D3 reflecting the abundance of the proteinmolecule that the particular mRNA is coding for. Secondly, that the CRC cell linesexpress all marker mRNAs except POSTN, which instead is expressed at high levels inthe fibroblast cell line. Thirdly, that none of the markers is expressed to a significantdegree in immune cell lines. Fourthly, that CEACAM5 is expressed at similar levels inprimary CRC tumors and normal colon epithelial cells. Based on the latter finding andprevious knowledge (Ohlsson L. et al. Br. ]. Cancer, vol. 95, p. 218-225 (2006)),CEACAM5 was considered to be the preferable marker for cells originating from thelarge intestine. Moreover, its high expression level makes it a very sensitive marker fordetection of colorectal cancer cells in lymph nodes. Fifthly, MUC2 measures to whatextent a CRC tumor is mucinous or not, MUC2 being the dominant mucin in colon andrectum. Patients with mucinous tumors have a better prognosis than those with non-mucinous tumors (Byrd ]. C. and Bresalier R. S. Cancer Metastasis Review, vol. 23, p. 77-99 (204); Ohlsson L. et al. Int. ]. Cancer, vol. 130, p. 1833-1843 (2012)). Finally, incontrast to CEACAM5 and MUC2, both KLK6 and SLC35D3 were expressed in CRCtumors and most CRC lines but not in normal colon epithelial cells, i.e. they are ectopically expressed in CRC tumors. 11 Table 2. Primer sequences used in RT-PCR for cloning of cDNA and construction of RNAcopy standards for SLC35D3, POSTN, KLK6, MUC2, CEACAM5, and 18S rRNA Gene 3' primer sequence 5' primer sequence(reverse) (forward) SLC35D3 CAGCACTCCCGTGACGTAC CATCGGCGTCCTGGTTC(SEQ ID NO: 19) (SEQ ID NO: 20) POSTN CCCTTGCTTACTCCCTTTCTC ACAGCTCAGAGTCTTCGTATATCG(SEQ ID NO: 4) (SEQ ID NO: 5) KLK6 TGGATCACAGCCCGGA TACACCTCGGGCCACTTG(SEQ ID NO: 21) (SEQ ID NO: 22) MUC2 TAGTGTCCAGCTCCAGCATGA CCGGGCTGCTCATTGAGA(SEQ ID NO: 10) (SEQ ID NO: 23) CEACAM5 TGGCTAGGATGGTCTCGAT GGACCTATGCCTGTTTTGTCT(SEQ ID NO: 24) (SEQ ID NO: 25) 18S rRNA CGCTCCCAAGATCCAACTAC GTAATTCCAGCTCCAATAGCGTA(SEQ ID NO: 26) (SEQ ID NO: 17) 12 Table 3. Expression levels of SLC35D3, POSTN, KLK6, MUC2 and CEACAM5 mRNAs inprimary CRC tumor, normal Colon, normal colon epithelial cells, CRC cell lines, immune cell lines, a fibroblast cell line, CRC liver metastases and normal liver.
SOURCE n mRNA copies / 18S rRNA unitSLC35D3 POSTN KLK6 MUC2 CEACAM5Primary CRC tumors 56 0.1* 9.7 2.9 1.1 175(0.04-0.4) (4.6 - 22.2) (0.9 - 8.5) (03 - 4.2) (107- 283) CRC cell lines 1** LS174T 0 0 79 4.3 328 1 HT29 0.02 0 256 0.01 32 1 T84 0.7 0 316 0.5 33 1 HCT8 0.07 0 32 0.02 32 1 CaCo2 0.09 0.0009 0.4 0.04 3Normal Colon Tissue 5 0.02 5.9 0 9 222*Normal Colon ECs 5 0.0009 0.2 0 32 300PBMCs 1 0.06 0 0 0 0Activated PBMCs 1 0 0 0 0 0T cell line 1 Iurkat 0 0.009 0 0 0B cell lines 1 B6 + KR4 0 0 0 0 0Plasma cell line 1 U266 0 0.005 0 0 0Monocyte cell line 1 U937 0 0 0 0 0.005Granulocyte cell line 1 HL60 0 0 0 0 0Pre-erythrocyte cell line 1 K562 0.09 0.001 0 0 0Fibroblast cell line 1 FSU 0 5.5 0 0.004 0.0002Livermetastasis 2 0.07 22.6 2 0.003 78Normal liver 2 0 2.3 0 0.00004 0.01 * Median and interquartile range from the 25th to the 75th percentile. ** Cell lines and PBMCs, mean of 3determinations. ECs, purified epithelial cells; PBMCs, peripheral blood mononuclear cells; 0, < 0.00001mRNA copies/18S rRNA unit.
Application of combined biomarker mRNA analysis for predicting probability of CRC-death A clinical material of lymph nodes from 166 surgically treated patients with CRC representing all four TNM stages and with known CEACAM5 mRNA, KLK6 mRNA, MUC2mRNA and 18S rRNA expression levels was analyzed for expression levels of SLC35D3 mRNA and POSTN mRNA. ln total mRNA from more than 600 lymph nodes were analyzed. The mRNA values were normalized against 18S rRNA and expressed as mRNA copies/18S rRNA unit. Previous studies by our group have demonstrated that 18S rRNA is an excellent RNA species for normalization (Bas A. et al, Scand. ]. lmmunol., vol. 59, p. 13 566-573 (2004); Ohlsson L. et al. Int. ]. Cancer, vol. 130, p. 1833-1843 (2012)). The nodewith the highest mRNA expression level was used to represent the patient in furtheranalysis. This is in analogy with the present clinical practice that H&E positive nodes areconsidered informative, while H&E negative nodes are considered non-informativeexcept in the case when all nodes are negative. Figure 2 shows the result. The figurealso shows the mRNA values for lymph nodes from non-CRC control patients and thedashed line indicates the highest value of this control group. Lymph nodes from stage IIIand IV patients displayed a larger fraction of nodes with mRNA values above the cut-offlevel than nodes from stage I or II patients [SLC35D3: stage I = 18%, stage II = 9%, stageIII = 25%, and stage IV = 79%; POSTN: stage I =25%, stage II = 13%, stage III = 32%, andstage IV = 69%].
The results from analysis of SLC35D3- and POSTN mRNA expression levels were used incombination with the known expression levels for CEACAM5-, KLK6- and MUC2 mRNAin the same nodes ofthe CRC patients (Ohlsson L. et al. Br. ]. Cancer, vol. 95, p. 218-225(2006); Ohlsson L. Thesis, ISBN 978-91-7459-318-1 (2011); Ohlsson L. et al. Br. ].Cancer, vol. 107, p. 150-157 (2012)) for development ofthis invention. Cut-offlevelswere determined for the 5 biomarkers as follows: The patients were ranked accordingto the biomarker expression level in the highest lymph node and then divided into fivegroups of equal number of patients. The groups were compared with respect to disease-free survival using Cox regression analysis. From this analysis, the cut-off level wasdefined as the mRNA expression level at the 8th decile because, for all five markers, thegroups below the 8th decile did not differ significantly in disease-free survival. Patientswho died from causes other than CRC were considered as disease-free. Patients weredivided into two groups, mRNA expression value above and mRNA expression valuebelow the cut-off and for each group the mean survival time after surgery was calculatedby cumulative survival analysis according to Kaplan-Meier and risk for recurrence ofCRC estimated according to univariate Cox regression analysis. The result for the fivebiomarkers is shown in Table 4. As can be seen, mRNA values above the cut-off levels for all of them were correlated with poorer prognosis with highly significant P-values. 14 Table 4. Comparative analysis of average Survival time and risk for recurrence ofdisease of CRC patients with biomarker (+) or biomarker (-) lymph nodes Biomarker mRNA Survival time after surgery Risk for recurrence of(copies/18S (months) CRCrRNA unit)Level Average Difference vs P-Value Hazard ratio P-valuemarker (-) SLC35D3 (_) <0.0059* 103** SLC35D3 (+) >0.0059 54 49 0.002 2.48*** 0.002POSTN (-) <11.05 107 POSTN (+) >11.05 76 31 0.001 2.52 0.002KLK6 (-) <0.0831 110 KLK6 (+) >0.0831 46 64 <0.0001 4.01 <0.0001MUC2 (-) <0.0045 108 MUC2 (+) >0.0045 64 44 0.001 2.53 0.001CEA (-) <4.2 112 CEA (+) >4.2 44 68 <0.0001 4.67 <0.0001 * The cut-off level is the 8th decile of the patient population.
** Mean survival time after surgery as calculated by cumulative survival analysis according to Kaplan-Meier.
*** Risk ratio as calculated according to univariate Cox regression analysis.Determining the levels for all five biomarkers and combining the differentmeasurements achieves further differentiation of the patient groups with respect tosurvival. ln one embodiment of the invention the combined information derived fromthe biomarker analysis to predict survival after surgery is used as follows: For eachhighest lymph node the values for the biomarkers, SLC35D3, KLK6 and MUC2 is firstdivided by their corresponding CEACAM5 value. For SLC35D3/CEACAM5 andKLK6/CEACAM5 the ratios were then referred to one oftwo groups >0.00001 or <0.00001 (Figure 3). The former group was assigned a value of 1 and the latter a value of0. For MUC2/CEACAM5 the division was achieved at a ratio of 3.0 assigning nodes withvalues above 3.0 a value of 1 and below a value of 0 (Figure 3). For POSTN thePOSTN/18S rRNA ratio and the clinical cut-off (8.0 copies/18S rRNA unit; Figure 2)were use to achieve the two groups, assigning values of 1 above the clinical cut-off and 0for below. A formula, (Formula A: SLC35D3/CEACAM5 + KLK6/CEACAM5 + POSTN/18SrRNA -MUC2/CEACAM5) was used to classify each patient into one of five groups(formula result: -1, 0, +1, +2, +3) and cumulative survival analysis according to Kaplan-Meier was performed on these groups. The result is shown in Figure 4. Five differentcurves are obtained. Group (-1) and (0) show good 3 and 5 years survival, group (+ 1) and (+2), relatively poor survival and group (+3) very poor survival (Table 5). The risk ratios calculated according to univariate Cox regression analysis, for groups (0), (+1), (+2) and (+3) in comparison to group (-1), is shown in Table 6. ln other embodiments of the invention the biomarker mRNA measurements werecalculated in the same way as in Formula A except that in these formulas, e.g. Formula Bto Formula E, one of the terms was systematically excluded. Figure 5 shows thecumulative survival according to Kaplan-Meier calculated according to formula E.Table 5 summarizes 3 and 5 years survival for biomarker mRNA measurements asdetermined by the 5 formulas (Formula A to Formula E) and Table 6 summarizes thehazards ratios for biomarker mRNA measurements as determined by Formula A, B andC. Although useful information with respect to survival after surgery is generated bybiomarker data treated according to formula B to formula E it is clear that treating thebiomarker mRNA data according to Formula A is the most informative demonstrating that all of these biomarkers contribute to the result.
Table 5. Percentage of CRC patients that have died from cancer 3 and 5 years aftersurgery as determined by cumulative survival according to Kaplan-Meier.Comparison between patients classified into groups according to formula A, B, C, Dand E.
FormulaA | B | c | D | E A | B | c | D | EGroup 3 years 5 years-1 7 10 5 - 10 14 15 12 - 180 10 13 14 9 10 20 26 21 15 19 +1 28 31 34 20 29 37 38 42 32 38 +2 42 57 41 51 42 47 84 80 58 65 +3 56 - 34 84 - 60 - Formula A: [SLC35D3/CEACAM5+POSTN/18S rRNA+KLK6/CEACAM5-MUC2/CEACAM5] giving the groups-1, 0, +1, +2, +3 Formula B: [SLC35D3/CEACAM5+POSTN/18S rRNA-MUC2/CEACAM5] giving thegroups -1, 0, +1, +2 Formula C: [KLK6/CEACAM5+POSTN/18S rRNA-MUC2/CEACAM5] giving thegroups -1, 0, +1, +2 Formula D: [SLC35D3/CEACAM5+KLK6/CEACAM5 +POSTN/18S rRNA] giving thegroup 0, +1, +2, +3 Formula E: [SLC35D3/CEACAM5+KLK6/CEACAM5-MUC2/CEACAM5] giving thegroups -1, 0, +1, +2. 16 Table 6. Risk for recurrence of CRC after surgery as calculated according to univariateCox regression analysis. Comparison between patients classified into groups accordingto formula A, B and C.
Formula A Formula B Formula CGroup Hazards P-value Hazards P-value Hazards P-valueratio ratio ratio _1 >1< >1< >1<0 1.33 ns 0.49 ns 0.41 ns+1 3.15 0.028 2.34 ns 3.3 0.008+2 3.64 0.021 5.56 0.001 6.59 <0.0001+3 6.98 0.001 Formula A: [SLC35D3/CEACAM5+POSTN/18S rRNA+KLK6/CEACAM5-MUC2/CEACAM5] giving the groups -1, 0, +1, +2, and +3 Formula B: [POSTN/18S rRNA+SLC/CEACAM5-MUC2/CEACAM5] giving the groups -1, 0, +1, +2 Formula C: [POSTN/18S rRNA+KLK6/CEACAM5-MUC2/CEACAM5] giving the groups-1, 0, +1 and +2.
A kit for determination of biomarker mRNAsThe invention also includes a kit for analysis of biomarker mRNA and 18S rRNA andtransformation of raw data to clinically useful information as illustrated by formulas Formula A to Formula E.
In one embodiment of the invention the particular forward and reverse primers as wellas probe sequences given in Table 1 are used in real-time quantitative RT-PCR.Quantitation is achieved by using specific copy standards (RNA) and 3' primers forreverse transcription with biomarker mRNA values normalized to content of 18S rRNAand /or content of CEACAM5 mRNA in the sample. Normalized values are allocated toone oftwo groups, either (1 =high risk for recurrence) and (0 = low risk for recurrence)according to the biomarker level with cut-off levels determined from analysis of aclinical material of lymph nodes from surgically treated CRC patients. Using aspecifically designed algorithm the (1) and (O) values for each biomarker is transformedto an estimate of relative risk of cancer death, with a range -1, 0, +1, +2, +3, where -1stands for the lowest risk and +3 for the highest risk, based on the formula: SLC35D3/CEACAM5 + KLK6/CEACAM5 + POSTN/18S rRNA -MUC2/CEACAM5.
In the embodiments ofthe invention as exemplified in Figures 4 and 5 and Tables 5 and 6 only the information from the lymph node with the highest biomarker mRNA is 17 value. However, a number of patients have more than one lymph node harboring tumorcells. The invention will also be used in this case, i.e. for differentiation between N1 and N2 stage patients, adding prognostic value.
EXAMPLES General methods Bioinformatics Analysis - Results from microarray gene expression analysis wereanalyzed by using lllumina Beadstudio software (version 3.3) for direct hybridizationassays. lntensity data were normalized by Beadstudios cubic spline algorithm withsubtracted background. Significant difference in expression was calculated usingBeadstudio software Error Model lllumina Custom with multiple testing correctionsusing Benjamini and Hochberg False Discovery Rate (Reiner A. et al. Bioinformatics, vol.19, p. 368-375 (2003)). Difference in gene expression was calculated as fold change, dividing the signal in the CRC samples of interest over average signal of controls.
Cell lines and peripheral blood mononuclear cells - The following established human celllines were utilized: LS174T, HT29, T84, HCT8 and CaCo2 (all colon carcinomas), Iurkatand Molt-4 (T-cell lymphomas), B6 and KR4 (EBV-transformed B cell lines), U266(plasmacytoma), U937 (monocyte-like cell line), K562 (erythroblastoid cell line), HL60(granulocyte cell line), FSU (fibroblast cell line). Peripheral blood mononuclear cells(PBMCs) were isolated from peripheral blood of healthy adults by Ficoll-lsopaquegradient centrifugation. PBMCs were activated in vitro by incubation with the OKT3monoclonal antibody (50 ng/ml) in HEPES-buffered RPMI 1640 supplemented with04% human serum albumin. PBMCs from seven individuals were incubated with thestimulus in parallel cultures for 4, 7, 20, 48 and 72 hours, washed, pooled and RNA extracted.
Clinical Characteristics ofthe CRC patients and Controls - Surgery for treatment of CRCwas carried out in 166 patients [81 men, 85 women, median age 72, (range 42-90)years]. Thirteen of the tumors were located in rectum and 153 in the colon. Seven oftherectal cancer patients received 25 Gy of preoperative radiotherapy. A locally radical tumor resection was carried out in all patients. The tumor differentiation grade was 18 poor, moderate and high in 11, 145 and 10 tumors, respectively. Routine hematoxylinand eosin (H&E) staining was performed on 2,351 lymph nodes, giving a median of 13(range 1-51) nodes per patient. According to the TNM classification, 30 patients were instage I (T1-2NOM0), 74 in stage II (T3-4NOM0), 46 in stage III (anyTN1-2M0) and 16 instage IV (anyTanyNM 1). Thirty-four patients (4 in stage II, 19 in stage III and 11 in stageIV) received chemotherapy after surgery. The median follow-up time was 75 (range 33- 147) months and no patient was lost at follow-up.
Controls included 18 men and 5 women [median age 25 years, (range 10-61)]undergoing surgery for ulcerative colitis (n=18), Crohn's colitis (n=3), rectal prolapse (n=1), and colon lipoma (n=1).
Informed consent was obtained from the patients and in one case his parents. TheResearch Ethics Committee of the Medical Faculty, Umeå University, Sweden approved the study.
Primary and distant CRC tumor and normal colon tissue - One hundred and thirteensamples from 85 primary CRC tumors were analyzed for biomarker mRNA levels (22samples from 16 stage I patients, 44 samples from 35 stage II patients, 41 samples from25 stage II patients, and 8 samples from 8 stage IV patients). Primary tumor stagedistribution (pT1-pT4) was 2, 14, 55 and 13 respectively. The differentiation grade waspoor in 11 tumors, moderate in 71 tumors and high in 3 tumors. One to four samples,approximately 0.5 x 0.5 x 0.5 cm in size, were collected from primary tumor specimensimmediately after resection, snap-frozen, and stored at -70°C until RNA extraction. Sixnormal colon samples, retrieved from the proximal or distal resection margin and twodistant liver metastasis samples were collected and treated in the same way as the primary CRC tumors.Epithelial cells from colon tissue - Colonic epithelial cells (ECs) were isolated from the normal colon mucosa at the resection margins as described (Fahlgren A. et al. Clin. Exp.
Immunol., vol. 131, p. 90-101 (2003)). 19 Lymph nodes - Lymph nodes were retrieved from the resected specimens and bisectedwith separate, sterile knives. One half of each node was fixed in 10% buffered formalinfor routine H&E-staining. The other half was snap frozen in liquid nitrogen and stored at-70°C until RNA extraction. From CRC patients, 503 lymph nodes (91, 253, 107 and 52nodes from stage I-IV patients, respectively) were collected. A median of 2 (range 1-15) lymph nodes was obtained per patient.
From control patients, 108 lymph nodes (82, 9, 13 and 4 nodes from ulcerative colitis, Crohn's colitis, colon lipoma and rectal prolapse patients, respectively) were collected.
RNA isolation - Total RNA was extracted from lymph nodes, normal and tumor colontissues, colon epithelial cells, PBMCs and cell lines using the acid guanidine phenolchloroform method (Chomczynski P and Sacchi N. Analyt. Biochem., vol. 162, p. 156-159(1987)) by adding 0.5 ml ofa solution containing 4 M guanidinium thiocyanate, 25 mMsodium citrate (pH 7.0), 0.5% sarcosyl and 0.1 M 2-mercaptoethanol per 25 mg tissueand up to 2.5 x 106 cells in the first homogenization step. Extracted RNA was dissolvedin RNAse-free water containing the RNAse inhibitor RNAsin (lU/ul; Promega, Madison,Wl). The RNA concentration was measured in a NanoDrop ND-1000 Spectrophotometer(NanoDrop Technologies) and for bead microarray analysis the integrity of the RNA was analyzed in a 2100 Bioanalyzer using an RNA nano assay (Agilent Technologies).
Preparation of RNA copy standards - Total RNA from a primary CRC tumor, two lymphnodes from two patients with CRC and the colon carcinoma cell lines LS174T and T84were used as starting material for copy standard preparations. The primers used for RT-PCR are given in Table 2.. The PCR products, which include the respective sequencesamplified in quantitative RT-PCR, were cloned, sequenced and used as template for inVitro transcription with T7 polymerase/RiboProbe ln Vitro Transcription Systems(Promega). Linearized DNA, 3-7 ug, was used in large-scale synthesis reactions carried out at 37°C for 2-3 hr. Thereaction products were then treated with 1 U/ug of RNase-free DNase (Promega) for 30-40 min at 37°C followed by extraction with phenol: chloroform: isoamylalcohol(25:24:1) and chloroform: isoamylalcohol (24:1). RNA was precipitated with 2.5 volumes of 99.5% ethanol and 0.5 volumes of 7.5 M ammonium acetate at -70°C for at least one hr. DNase treatment was repeated at least twice. Finally the copy standardswere checked by RT-PCR and PCR to evaluate the content of DNA, which proved to beless than 0.2% for all of them. Concentration of the transcripts was calculated on thebasis ofthe ODzeo value, the molecular weight ofthe transcript and Avogadro's number.
The standards were finally diluted to 108 copies/ ul.
Real-time qRT-PCR - Real-time qRT-PCR assays with RNA copy standards wereconstructed for SLC35D3, POSTN, KLK6, CEACAM5, and MUC2 using the Tacman EZ RT-PCR technology (Applied Biosystems Foster City Ca). Primer and probe sequences areshown in Table 1. The RT-PCR profile was 49° C for 2 min, 59° C for 30 min, 94° C for 5min, followed by 45 cycles of93° C for 20 sec and 61° C for 1 min. Serial dilutions of therespective RNA copy standard at concentrations from 103 to 108 copies/ ul wereincluded in each analysis. All qRT-PCR analyses were carried out in triplicates. Emissionfrom released reporter dye was monitored by the ABI Prism 7900 Sequence DetectionSystem (Perkin-Elmer, Wellesley, Ma). For normalization of mRNA levels, theconcentration of 18S rRNA was determined in each sample by real-time qRT-PCRaccording to the manufacturer's protocol (Applied Biosystems) or by use of primers andprobe given in Table 1 (SEQ ID NO: 16-18) and copy standard prepared by using theprimers given in Table 2 (SEQ ID NO: 26,17). Results were expressed as mRNA copiesper unit of 18S rRNA or as RNA copies per copy of 18S rRNA in both cases yielding directly comparable levels of biomarkers.
Statistical Analysis - Differences in disease free survival and risk for recurrent diseaseafter surgery between patients groups were calculated according to Kaplan-Meiersurvival model in combination with the log rank test and univariate Cox regressionanalysis. Differences in survival time and hazards ratios with a P value <0.05 were considered to be statistically significant. The software utilized was SPSS (version 18). 21

Claims (23)

1. ) A method of determining the metastatic potential and/or tumor aggressiveness of a colorectal cancer in a subject, comprising the steps: a) b) determining the gene expression levels of genes SLC35D3, and POSTN in aregional lymph node sample obtained from the subject; and comparing the gene expression levels determined in step a) with thereference gene expression levels of the same genes in a reference patient population; wherein higher expression levels of the genes SLC35D3 and POSTN compared to the reference are associated with an increased metastatic potential and /or tumor aggressiveness.
2. ) A method according to claim 1, comprising the steps: a) b) determining the gene expression levels of genes SLC35D3, POSTN, andKLK6 in a regional lymph node sample obtained from the subject; andcomparing the gene expression levels determined in step a) with thereference gene expression levels of the same genes in a reference patient population; wherein higher expression levels ofthe genes SLC35D3, POSTN, and KLK6 compared to the reference are associated with an increased metastatic potential and /or tumor aggressiveness.3) A method according to claim 1, comprising the steps:a) determining the gene expression levels of genes SLC35D3, POSTN, and b)
3. MUC2 in a regional lymph node sample obtained from the subject; andcomparing the gene expression levels determined in step a) with thereference gene expression levels of the same genes in a reference patient population; wherein higher expression levels of the genes SLC35D3, POSTN, and MUC2 compared to the reference are associated with an increased metastatic potential and/or tumor aggressiveness. 23
4. ) A method according to claims 1, 2 and 3 comprising the steps: a) b) determining the gene expression levels of genes SLC35D3, POSTN, KLK6,and MUC2 in a regional lymph node sample obtained from the subject;and comparing the gene expression levels determined in step a) with thereference gene expression levels of the same genes in a reference patient population; wherein higher expression levels ofthe genes SLC35D3, POSTN, KLK6, and MUC2 compared to the reference are associated with an increased metastatic potential and /or tumor aggressiveness.
5. ) A method according to claim 4, further comprising the steps: C) d) determining the gene expression level of the gene CEACAM5 and thelevel of 18S rRNA in said sample ; based on the results obtained in steps a) and c) calculating the ratiosSLC35D3/CEACAM5, KLK6/CEACAM5, POSTN/18S rRNA, andMUC2/CEACAM5; giving the ratios obtained in step d) the values of (+1) or (0) dependingon whether said ratio is larger than a cut-off value based on the sameratio in said reference patient population, and where ratios higher thanthe cut-off value obtain a value of (+ 1) and values lower than the cut-offlevel obtain a value of (0); and calculating an index A using the ratios obtained in step e) and using theformula [A = SLC35D3/CEACAM5 + KLK6/CEACAM5 + POSTN/18S rRNA- MUC2/CEACAM5]; wherein an index (+3) is associated with very high metastatic potential and /or tumor aggressiveness, the index (+2) and (+ 1) with high metastatic potential and /or tumor aggressiveness, and the index (0) and (-1) with low metastatic potential and /or tumor aggressiveness.
6. ) The method according to claim 5 wherein said cut-off values is the ratios of the 7th decile of said reference patient population, the ratios of the 3rd quartile of 24
7. )
8. )
9. )
10. )
11. ) said reference patient population, or the ratios of the 8th decile of said reference patient population. A method of determining the metastatic potential and/ or tumor aggressivenessof a colorectal cancer in a subject, comprising: a) determining the gene expression levels of the genes SLC35D3, KLK6,MUC2 and CEACAM5 in a primary intestinal tumor, blood, or feces sampleobtained from the subject; b) based on the result obtained in step a) calculating the ratiosSLC35D3/CEACAM5, KLK6/CEACAM5 and MUC2/CEACAM5; and c) comparing the ratios determined in step b) with reference ratioscalculated from expression levels of the same genes in a reference patientpopulation; wherein the ratios SLC35D3/CEACAM5 and KLK6/CEACAM5 are associated with an increased metastatic potential and/ or tumor aggressiveness and the ratio MUC2/CEACAM5 is associated with decreased metastatic potential and/or tumor aggressiveness. The method according to any of claims 1 to 7, wherein the gene expression levels are determined by quantifying the amount of mRNA expressed from said genes. The method according to claim 8, wherein said amount of mRNA is determined by hybridization, sequencing or quantitative RT-PCR. The method according to claim 9, wherein said amount of mRNA is determinedby use of a method selected from microarray and bead array technologies,transcriptome sequencing, real time quantitative RT-PCR, multiplex quantitative RT-PCR. The method according to any of claims 8 to 10, wherein said amount of mRNA is determined using an RNA or DNA copy standard.
12. )
13. )
14. )
15. )
16. )
17. ) A method for determining the prognosis of a subject diagnosed with colorectalcancer and having a tumor, said method comprising the steps:a) determining the metastatic potential and/ or tumor aggressiveness usingthe method according to any of the claims 1 to 11 ; andb) determining that the subject has a good prognosis if the metastaticpotential and/ or tumor aggressiveness is low, ordetermining that the subject has a poor prognosis if the metastatic potential and/or tumor aggressiveness is high. The method of claim 12, wherein the poor prognosis is a decrease in the likelihood of survival compared to the good prognosis. A method for determining the treatment for a subject diagnosed with colorectalcancer and having a tumor, said method comprising the steps:a) determining the metastatic potential and/or tumor aggressiveness usingthe method according to any of the claims 1-11; andb) determining the treatment for said subject dependent on the result obtained in step a). The method of claim 14, wherein said treatment is to give postoperativetreatment, e.g. chemotherapy, to a patient determined to have a high metastatic potential and/ or tumor aggressiveness. The method of claim 14, wherein said treatment is to abstain from postoperativetreatment to a patient with a low metastatic potential and /or tumor aggressiveness. A kit for determining metastatic potential and/or tumor aggressiveness of asubject diagnosed with colorectal cancer, comprising nucleic acid primers andprobes for determination of the gene expression levels, of one or more ofthe genes CEACAM5, KLK6, POSTN, SLC35D3, and MUC2 and the level of 18S rRNA. 26
18. ) The kit according to claim 17, wherein the nucleic acid primers and probes are selected from those given in Table 1.
19. ) The kit according to any of claims 17 to 18, further comprising, mRNA, RNAand/or DNA copy standards. 27
SE1630095A 2016-04-20 2016-04-20 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor SE540173C2 (en)

Priority Applications (9)

Application Number Priority Date Filing Date Title
SE1630095A SE540173C2 (en) 2016-04-20 2016-04-20 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor
CN201780024184.7A CN109073651A (en) 2016-04-20 2017-04-12 The marker gene of colorectal cancer classification judges lymphatic metastasis in the method for prognosis colorectal cancer and for its kit
EP17786247.1A EP3446122B1 (en) 2016-04-20 2017-04-12 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor
US16/093,013 US10988811B2 (en) 2016-04-20 2017-04-12 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor
AU2017254347A AU2017254347B2 (en) 2016-04-20 2017-04-12 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor
KR1020187029589A KR102353374B1 (en) 2016-04-20 2017-04-12 Marker gene for colorectal cancer classification, method for determining lymph node metastasis for prognosis of colorectal cancer, and kit therefor
JP2018554694A JP6968822B2 (en) 2016-04-20 2017-04-12 Marker genes for the classification of colorectal cancer, methods for determining lymph node metastasis in the prognosis of colorectal cancer, and kits for it
PCT/SE2017/050368 WO2017184059A1 (en) 2016-04-20 2017-04-12 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor
US17/210,768 US20210246513A1 (en) 2016-04-20 2021-03-24 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
SE1630095A SE540173C2 (en) 2016-04-20 2016-04-20 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor

Publications (2)

Publication Number Publication Date
SE1630095A1 true SE1630095A1 (en) 2017-10-21
SE540173C2 SE540173C2 (en) 2018-04-24

Family

ID=60116279

Family Applications (1)

Application Number Title Priority Date Filing Date
SE1630095A SE540173C2 (en) 2016-04-20 2016-04-20 Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor

Country Status (8)

Country Link
US (2) US10988811B2 (en)
EP (1) EP3446122B1 (en)
JP (1) JP6968822B2 (en)
KR (1) KR102353374B1 (en)
CN (1) CN109073651A (en)
AU (1) AU2017254347B2 (en)
SE (1) SE540173C2 (en)
WO (1) WO2017184059A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111781356A (en) * 2019-04-04 2020-10-16 清华大学 Gastric cancer very early cell marker and gastric precancerous lesion early cell marker and application thereof in diagnostic kit

Family Cites Families (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6773882B2 (en) * 2000-05-01 2004-08-10 Gen-Probe, Incorporated Polynucleotide probes for detection and quantitation of candida species
WO2006015209A2 (en) * 2004-07-29 2006-02-09 Stem Cell Innovations, Inc. Differentiation of stem cells
WO2007096142A2 (en) * 2006-02-22 2007-08-30 Philogen Spa Vascular tumor markers
US20100009905A1 (en) 2006-03-24 2010-01-14 Macina Roberto A Compositions and Methods for Detection, Prognosis and Treatment of Colon Cancer
US9353415B2 (en) * 2006-12-19 2016-05-31 Thomson Reuters (Scientific) Llc Methods for functional analysis of high-throughput experimental data and gene groups identified therefrom
JPWO2009044899A1 (en) * 2007-10-03 2011-02-17 協和発酵キリン株式会社 Nucleic acids that control cell growth
KR101007567B1 (en) * 2007-10-30 2011-01-14 한국생명공학연구원 Colon cancer diagnostic markers using up-regulated genes
EP2265730B1 (en) * 2008-03-12 2018-06-06 The Rockefeller University Methods and compositions for translational profiling and molecular phenotyping
EP2380025B1 (en) * 2009-01-14 2013-09-11 The United States of America, as represented by The Secretary, Department of Health and Human Services Ratio based biomarkers and methods of use thereof
US20120282167A1 (en) * 2009-08-10 2012-11-08 Institut Curie Method for predicting the sensitivity of a tumor to an epigenetic treatment
US20140148348A1 (en) * 2010-01-13 2014-05-29 Christine Kuslich Dectection of gastrointestinal disorders
WO2012009547A2 (en) * 2010-07-14 2012-01-19 The Regents Of The University Of California Biomarkers for diagnosis of transient ischemic attacks
US8741905B2 (en) 2010-11-05 2014-06-03 The Broad Institute, Inc. Compounds and methods for treating autoimmune diseases
EP2665835B1 (en) * 2011-01-18 2018-03-14 Everist Genomics, Inc. Prognostic signature for colorectal cancer recurrence
AU2012301664A1 (en) * 2011-08-31 2014-02-27 Oncocyte Corporation Methods and compositions for the treatment and diagnosis of cancer
AU2012301589A1 (en) * 2011-08-31 2014-02-27 Oncocyte Corporation Methods and compositions for the treatment and diagnosis of colorectal cancer
WO2013052480A1 (en) * 2011-10-03 2013-04-11 The Board Of Regents Of The University Of Texas System Marker-based prognostic risk score in colon cancer
JP5805518B2 (en) * 2011-12-21 2015-11-04 株式会社島津製作所 Multiplex colorectal cancer marker panel
WO2015120069A1 (en) * 2014-02-04 2015-08-13 Beth Israel Deaconess Medical Center, Inc. Methods and kits for the diagnosis and treatment of pancreatic cancer

Also Published As

Publication number Publication date
SE540173C2 (en) 2018-04-24
JP6968822B2 (en) 2021-11-17
AU2017254347B2 (en) 2023-04-20
KR20180134896A (en) 2018-12-19
US20190136328A1 (en) 2019-05-09
US10988811B2 (en) 2021-04-27
EP3446122C0 (en) 2024-03-27
AU2017254347A1 (en) 2018-10-18
JP2019514365A (en) 2019-06-06
EP3446122A4 (en) 2020-01-08
EP3446122B1 (en) 2024-03-27
WO2017184059A1 (en) 2017-10-26
KR102353374B1 (en) 2022-01-18
US20210246513A1 (en) 2021-08-12
CN109073651A (en) 2018-12-21
EP3446122A1 (en) 2019-02-27

Similar Documents

Publication Publication Date Title
Hogan et al. Integrated genomic analysis of relapsed childhood acute lymphoblastic leukemia reveals therapeutic strategies
US20190300963A1 (en) Mirna expression signature in the classification of thyroid tumors
US20150376717A1 (en) Methods and kits for detecting melanoma
Ogino et al. Combined analysis of COX-2 and p53 expressions reveals synergistic inverse correlations with microsatellite instability and CpG island methylator phenotype in colorectal cancer
MX2008011839A (en) Propagation of primary cells.
WO2015073949A1 (en) Method of subtyping high-grade bladder cancer and uses thereof
US20110223180A1 (en) Methods and compositions related to a multi-methylation assay to predict patient outcome
US20120282167A1 (en) Method for predicting the sensitivity of a tumor to an epigenetic treatment
EP2499258A1 (en) Signature for the diagnosis of breast cancer aggressiveness and genetic instability
Kastenhuber et al. Quantitative assessment of intragenic receptor tyrosine kinase deletions in primary glioblastomas: their prevalence and molecular correlates
Ceppi et al. Excision repair cross complementing-1 and topoisomerase IIα gene expression in small-cell lung cancer patients treated with platinum and etoposide: a retrospective study
Jang et al. Prognostic significance of EPHB2 expression in colorectal cancer progression
AU2010264763B2 (en) Molecular markers in kidney cancer
US20210246513A1 (en) Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor
WO2017221927A1 (en) Mmp1 gene transcript for use as marker for diagnosis of ovarian cancer prognosis, and test method
US20090297506A1 (en) Classification of cancer
Brand et al. Association of polymorphisms in TGFB1 and prostate cancer prognosis
US20160304961A1 (en) Method for predicting the response to chemotherapy treatment in patients suffering from colorectal cancer
Stathopoulos et al. Differences in gene expression between individuals with multiple primary and single primary malignancies
ES2631193T3 (en) Tumor markers
García-Carbonero et al. Method for predicting the response to chemotherapy treatment in patients suffering from colorectal cancer
CN113278702A (en) Application of PSMC2 gene detection primer in preparation of glioblastoma multiforme auxiliary diagnosis and prognosis evaluation kit
TURKINGTON et al. Future Directions: Gene Expression Profiling
Kottorou et al. 764 Increased expression of NFY-C (Nuclear Factor Y, subunit C) and RORA (Retinoic acid receptor-related Orphan Receptor Alpha) in colorectal adenocarcinoma
WO2016203476A1 (en) Methods and compositions for diagnosing and treating urothelial cancer